基于LangChain手工测试用例转App自动化测试生成工具

打开  app activity ".Settings" , app package com.android.settings
2. 点击 Battery
3. 获取 Battery 的电量
4. 返回上一级页面

from time import sleep
from appium import webdriver
from appium.options.android import UiAutomator2Options
from appium.webdriver.common.appiumby import AppiumBy

class AppAutoFramework:
    def __init__(self):
        self.driver = None
        self.element = None

    def init(self, app_activity, app_package):
        if not self.driver:
            # 设置 capability
            caps = {
                # 设置 app 安装的平台（Android、iOS）
                "platformName": "android",
                # 设置 appium 驱动
                "appium:automationName": "uiautomator2",
                # 设置设备名称
                "appium:deviceName": "emulator-5554",
                "appium:noReset": True,
                # 设置以下两个参数来控制启动app和关闭掉app
                "appium:forceAppLaunch" : True,
                "appium:shouldTerminateApp" : True,
                # 设置 app 的包名
            "appium:appPackage": app_package,
                # 设置 app 启动页
            "appium:appActivity": app_activity
            }
            # 初始化 driver
            self.driver = webdriver.Remote(
                "http://localhost:4723",
                options=UiAutomator2Options().load_capabilities(caps)
            )
            self.driver.implicitly_wait(5)
        return self.source()

    def source(self):
        return self.driver.page_source

    def find(self, locator):
        print(f"find xpath = {locator}")
        element = self.driver.find_element(by=AppiumBy.XPATH, value=locator)
        self.element = element
        return self.source()

    def click(self):
        self.element.click()
        sleep(1)
        return self.source()

    def send_keys(self, text):
        self.element.clear()
        self.element.send_keys(text)
        return self.source()

    def back(self):
        self.driver.back()
        return self.source()

import time

from langchain_core.tools import tool

app = AppAutoFramework()


@tool
def init(app_activity, app_package):
    """
    打开app的安装包，并返回app的resource
    """
    return app.init(app_activity, app_package)


@tool
def find(xpath: str):
    """通过xpath定位元素"""
    return app.find(xpath)


@tool
def click(xpath: str = None):
    """以xpath的方式定位网页元素后点击"""
    app.find(xpath)
    return app.click()


@tool
def send_keys(xpath, text):
    """定位到xpath指定的元素，并输入text"""
    app.find(xpath)
    return app.send_keys(text)


@tool
def sleep(seconds: int):
    """等待指定的秒数"""
    time.sleep(seconds)


@tool
def back():
    """
    返回上一级界面
    :return:
    """
    app.back()


tools = [init, find, click, send_keys, sleep, back]

# 获取执行结果
import json
from langchain import hub
from langchain.agents import create_structured_chat_agent, AgentExecutor
from langchain_core.agents import AgentAction
from langchain_openai import ChatOpenAI

from app.appium_tools import tools

prompt = hub.pull("hwchase17/structured-chat-agent")
llm = ChatOpenAI()
app_agent = create_structured_chat_agent(llm, tools, prompt)
# Create an agent executor by passing in the agent and tools
app_agent_executor = AgentExecutor(
    agent=app_agent, tools=tools,
    verbose=True,
    return_intermediate_steps=True,
    handle_parsing_errors=True)

query = """
你是一个自动化测试工程师，接下来需要根据测试步骤，
每一步如果定位都是根据上一步的返回的html操作完成
执行对应的测试用例，测试步骤如下
1. 打开  app activity ".Settings" , app package com.android.settings
2. 点击 Battery
3. 获取 Battery 的电量
4. 返回上一级页面
"""

def execute_result(_):
    # 获取执行结果
    r = app_agent_executor.invoke({"input": query})
    # 获取执行记录
    steps = r["intermediate_steps"]
    steps_info = []
    # 遍历执行步骤，获取每一步的执行步骤以及输入的信息。
    for step in steps:
        action = step[0]
        if isinstance(action, AgentAction):
            steps_info.append({'tool': action.tool, 'input': action.tool_input})
    return json.dumps(steps_info)


if __name__ == '__main__':
    print(execute_result(""))

prompt_testcase = PromptTemplate.from_template("""
你是一个app自动化测试工程师，主要应用的技术栈为pytest + appium。
以下为app自动化测试的测试步骤，测试步骤由json结构体描述

{step}

{input}

""")

chain = (
        RunnablePassthrough.
        assign(step=execute_result)
        | prompt_testcase
        | llm
        | StrOutputParser()
)

print(chain.invoke({"input": "请根据以上的信息，给出对应的app自动化测试的代码"}))